%0 Dataset
%T A dataset of blowing snow event visibility classification for the Makitasi Wind Zone, China, 2024–2025
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/0b7968f3-3dad-4ddc-8448-48843d675c3b
%W NCDC
%R 10.12072/ncdc.snow.db7564.2026
%A ma lei
%A hu zhi xuan
%A Zhao Jing
%A li peng bo
%A zhao qin
%A pan xing yu
%A li tai zhi
%K Mayitas Wind Zone;2024-2025;wind-blown snow;visibility classification;highway
%X Low visibility caused by wind-blown snow disasters is a key factor affecting high-grade highway traffic safety and operating efficiency. Refined visibility classification data is of great significance for model training, management and control strategy formulation, and roadside edge computing equipment deployment. This dataset is based on continuous videos from 4 roadside fixed surveillance cameras at the K264+700-K272+700 section of the G3015 Keta Expressway in Mayitas Wind Area, Xinjiang from November 2024 to March 2025. Video time screening is carried out according to the observation data of the visibility meter, frame extraction is carried out at a frequency of 1 minute/frame, and is prepared using a manual hierarchical labeling method. The dataset consists of a compressed package, containing 8 folders, corresponding to 8 visibility levels (0-100m, 100-200m, 200-300m, 300-400m, 400-500m, 500-1000m, 1000-2000m, NULL). A total of 14679 roadside cameras captured images, with an image spatial resolution of 640×480 pixels. This dataset can be used to characterize the temporal and spatial distribution and change laws of highway visibility under wind-blown snow conditions, and serve traffic meteorological warning and highway dynamic management and control in wind-blown snow-prone areas.